Machine learning : ECML-94 : [7th] European Conference on Machine Learning, Catania, Italy, April 6 8, 1994 : proceedings
This volume contains the proceedings of the European Conference on Machine Learning 1994, which continues the tradition of earlier meetings and which is a major forum for the presentation of the latest and most significant results in machine learning. Machine learning is one of the most important su...
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| Format: | Livre numérique |
| Sprache: | Anglais |
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| Schriftenreihe: | Lecture notes in computer science. Lecture notes in artificial intelligence
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| Online Zugang: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
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Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Machine learning, ECML-94, European Conference on Machine Learning, Catania, Italy, April 6-8, 1994, proceedings, Francesco Bergadano, Luc De Raedt, eds, Berlin, Springer-Verlag, 1994, 1 vol. (xi, 438 p.), Lecture notes in computer science, 3-540-57868-4 • Machine Learning: ECML-94, Texte imprimé, 9783662204955 |
Inhaltsangabe:
- Industrial applications of ML: Illustrations for the KAML dilemma and the CBR dream
- Knowledge representation in machine learning
- Inverting implication with small training sets
- A context similarity measure
- Incremental learning of control knowledge for nonlinear problem solving
- Characterizing the applicability of classification algorithms using meta-level learning
- Inductive learning of characteristic concept descriptions from small sets of classified examples
- FOSSIL: A robust relational learner
- A multistrategy learning system and its integration into an interactive floorplanning tool
- Bottom-up induction of oblivious read-once decision graphs
- Estimating attributes: Analysis and extensions of RELIEF
- BMWk revisited generalization and formalization of an algorithm for detecting recursive relations in term sequences
- An analytic and empirical comparison of two methods for discovering probabilistic causal relationships
- Sample PAC-learnability in model inference
- Averaging over decision stumps
- Controlling constructive induction in CIPF: An MDL approach
- Using constraints to building version spaces
- On the utility of predicate invention in inductive logic programming
- Learning problem-solving concepts by reflecting on problem solving
- Existence and nonexistence of complete refinement operators
- A hybrid nearest-neighbor and nearest-hyperrectangle algorithm
- Automated knowledge acquisition for Prospector-like expert systems
- On the role of machine learning in knowledge-based control
- Discovering dynamics with genetic programming
- A geometric approach to feature selection
- Identifying unrecognizable regular languages by queries
- Intensional learning of logic programs
- Partially isomorphic generalization and analogical reasoning
- Learning from recursive, tree structured examples
- Concept formation in complex domains
- An algorithm for learning hierarchical classifiers
- Learning belief network structure from data under causal insufficiency
- Cost-sensitive pruning of decision trees
- An instance-based learning method for databases: An information theoretic approach
- Early screening for gastric cancer using machine learning techniques
- DP1: Supervised and unsupervised clustering
- Using machine learning techniques to interpret results from discrete event simulation
- Flexible integration of multiple learning methods into a problem solving architecture
- Concept sublattices
- The piecewise linear classifier DIPOL92
- Complexity of computing generalized VC-dimensions
- Learning relations without closing the world
- Properties of Inductive Logic Programming in function-free Horn logic
- Representing biases for Inductive Logic Programming
- Biases and their effects in Inductive Logic Programming
- Inductive learning of normal clauses.